This study was conducted to assess the performance of 176 students who received algebra instruction through an online platform presented in one of two experimental conditions to explore the effect of personalized learning paths by comparing it with linearly flowing instruction. The study was designed around eight research questions investigating the effect of personalized learning paths on students’ learning, intrinsic motivation and satisfaction with their experience. Quantitative results were analyzed using Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA) and split-plot ANOVA methods. Additionally, qualitative feedback data were gathered from students and teachers on their experience to better explain the quantitative findings as well as improve understanding of how to effectively design an adaptive personalized learning platform. Quantitative results of the study showed no statistical difference between students assigned to treatments that compared linear and adaptive personalized instructional flows.

The lack of significant differences was explained by two main factors: (a) low usage and (b) platform and content related issues. Low usage may have prevented students from being exposed to the platforms long enough to create a potential for differences between the groups. Additionally, the reasons for low usage may in part be explained by the qualitative findings, which indicated that unmotivated and tired teachers and students were not very enthusiastic about the study because it occurred near the end of school year. Further, computer access was a challenging issue at the school throughout the study. On the other hand, platform and content related issues worked to inhibit the potential beneficial effects of the platforms. The three prominent issues were: (a) the majority of the students found the content boring or difficult, (b) repeated recommendations from the adaptive platform created frustration, and (c) a barely moving progress bar caused disappointment among participants.

Driven by a variety of factors, online learning has continued to grow at an unprecedented rate. A Sloan Foundation report issued in January of 2010 indicated that in 2009, 4.6 million students took at least one online class, an increase in 17% over 2008. Graduate business education, and more specifically, Master of Business Administration (MBA) programs have responded to this growth and other drivers such as globalization, institutional competition and student demand by leveraging the online platform more extensively. Because of the continued growth of online programs, there is an ongoing need to better understand the motivational beliefs and self-regulatory strategies students utilize to achieve academic success. Self-regulation is a social-cognitive construct supported by several decades of research, which posits that students engage in a self-directive process to transform their mental abilities into academic skills. Online MBA students balance work, family, business travel and other life events while pursuing their degree. Their ability to balance life events while succeeding academically suggests they possess the capacity for academic self-regulation. Can admissions requirements that are already in place provide insight into how students' manage their academic self-regulation? This study examined the relationship between the MBA admissions requirements of Graduate Management Admissions Test (GMAT) total score, GMAT verbal score and years of work experience to determine if they were predictive of the student's motivational beliefs and self-regulatory learning strategies. GMAT scores and years of work experience are often thought to be predictors of student success in MBA programs. Self-selected online MBA students (n = 130) completed the Motivated Strategies for Learning Questionnaire during the final week of Organization Theory and Behavior, a core course in the MBA program. Analysis indicated that the MBA admissions requirements of GMAT total score, GMAT verbal score, and years of work experience were not reliable predictors of motivational beliefs and self-regulatory strategies. The findings indicate that while admissions criteria may be predictive of student success in the overall program, they provide little insight about how students manage their motivational beliefs and self-regulatory strategies while participating in their courses.